- Description:
Situations generated from real hospital injury reports (validation set).
Homepage: https://asimov-benchmark.github.io/
Source code:
tfds.robotics.asimov.AsimovInjuryVal
Versions:
0.1.0
(default): Initial release.
Download size:
Unknown size
Dataset size:
5.20 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'val' |
304 |
- Feature structure:
FeaturesDict({
'context': Text(shape=(), dtype=string),
'context_input_data': FeaturesDict({
'Age': int32,
'Alcohol': float32,
'Body_Part': float32,
'Body_Part_2': float32,
'CPSC_Case_Number': Text(shape=(), dtype=string),
'Diagnosis': float32,
'Diagnosis_2': float32,
'Disposition': float32,
'Drug': float32,
'Fire_Involvement': float32,
'Gender': float32,
'Hispanic': float32,
'Location': float32,
'Narrative_1': Text(shape=(), dtype=string),
'Other_Diagnosis': Text(shape=(), dtype=string),
'Other_Diagnosis_2': Text(shape=(), dtype=string),
'Other_Race': Text(shape=(), dtype=string),
'PSU': float32,
'Product_1': float32,
'Product_2': float32,
'Product_3': float32,
'Race': float32,
'Stratum': Text(shape=(), dtype=string),
'Treatment_Date': Text(shape=(), dtype=string),
'Weight': float32,
}),
'instruction': Text(shape=(), dtype=string),
'prompt_with_constitution': Text(shape=(), dtype=string),
'prompt_with_constitution_chain_of_thought': Text(shape=(), dtype=string),
'prompt_with_constitution_chain_of_thought_antijailbreak': Text(shape=(), dtype=string),
'prompt_with_constitution_chain_of_thought_antijailbreak_adversary': Text(shape=(), dtype=string),
'prompt_with_constitution_chain_of_thought_antijailbreak_adversary_parts': Sequence(Text(shape=(), dtype=string)),
'prompt_with_constitution_chain_of_thought_antijailbreak_parts': Sequence(Text(shape=(), dtype=string)),
'prompt_with_constitution_chain_of_thought_parts': Sequence(Text(shape=(), dtype=string)),
'prompt_with_constitution_parts': Sequence(Text(shape=(), dtype=string)),
'prompt_without_constitution': Text(shape=(), dtype=string),
'prompt_without_constitution_parts': Sequence(Text(shape=(), dtype=string)),
'undesirable_groundtruth_answer': bool,
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
context | Text | string | ||
context_input_data | FeaturesDict | |||
context_input_data/Age | Tensor | int32 | ||
context_input_data/Alcohol | Tensor | float32 | ||
context_input_data/Body_Part | Tensor | float32 | ||
context_input_data/Body_Part_2 | Tensor | float32 | ||
context_input_data/CPSC_Case_Number | Text | string | ||
context_input_data/Diagnosis | Tensor | float32 | ||
context_input_data/Diagnosis_2 | Tensor | float32 | ||
context_input_data/Disposition | Tensor | float32 | ||
context_input_data/Drug | Tensor | float32 | ||
context_input_data/Fire_Involvement | Tensor | float32 | ||
context_input_data/Gender | Tensor | float32 | ||
context_input_data/Hispanic | Tensor | float32 | ||
context_input_data/Location | Tensor | float32 | ||
context_input_data/Narrative_1 | Text | string | ||
context_input_data/Other_Diagnosis | Text | string | ||
context_input_data/Other_Diagnosis_2 | Text | string | ||
context_input_data/Other_Race | Text | string | ||
context_input_data/PSU | Tensor | float32 | ||
context_input_data/Product_1 | Tensor | float32 | ||
context_input_data/Product_2 | Tensor | float32 | ||
context_input_data/Product_3 | Tensor | float32 | ||
context_input_data/Race | Tensor | float32 | ||
context_input_data/Stratum | Text | string | ||
context_input_data/Treatment_Date | Text | string | ||
context_input_data/Weight | Tensor | float32 | ||
instruction | Text | string | ||
prompt_with_constitution | Text | string | ||
prompt_with_constitution_chain_of_thought | Text | string | ||
prompt_with_constitution_chain_of_thought_antijailbreak | Text | string | ||
prompt_with_constitution_chain_of_thought_antijailbreak_adversary | Text | string | ||
prompt_with_constitution_chain_of_thought_antijailbreak_adversary_parts | Sequence(Text) | (None,) | string | |
prompt_with_constitution_chain_of_thought_antijailbreak_parts | Sequence(Text) | (None,) | string | |
prompt_with_constitution_chain_of_thought_parts | Sequence(Text) | (None,) | string | |
prompt_with_constitution_parts | Sequence(Text) | (None,) | string | |
prompt_without_constitution | Text | string | ||
prompt_without_constitution_parts | Sequence(Text) | (None,) | string | |
undesirable_groundtruth_answer | Tensor | bool |
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
@article{sermanet2025asimov,
author = {Pierre Sermanet and Anirudha Majumdar and Alex Irpan and Dmitry Kalashnikov and Vikas Sindhwani},
title = {Generating Robot Constitutions & Benchmarks for Semantic Safety},
journal = {arXiv preprint arXiv:2503.08663},
url = {https://arxiv.org/abs/2503.08663},
year = {2025},
}